code: def classification_multi(self):
      from sklearn.metrics import accuracy_score
  
      true, pred_score = torch.cat(self._true), torch.cat(self._pred)
      pred_int = self._get_pred_int(pred_score)
      return {
          "accuracy": round(accuracy_score(true, pred_int), cfg.round)
      }
  
imports: import logging
  import math
  import sys
  import torch
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.utils.device import get_current_gpu_usage
  from graphgym.utils.io import dict_to_json, dict_to_tb, makedirs
label_desc: Use image node_id 9 for calling the Logger obj's underlying member method code with example usage: obj.classification_multi() and returns: dict